Senior Business And Marketing Data Scientist I

Minimum qualifications:Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.Preferred qualifications:Ability to share insights via documents and decks.Excellent written and communications skills. About the job In this role, you will get around obstacles to achieve the goal. You will be level-headed and can cut across organizations and processes to drive alignment and simplicity. You will have strong problem-solving skills that will drive clarity and enable smart decision-making for Global Business Organizations (GBO).The US base salary range for this full-time position is $150,000-$223,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google. Responsibilities Lead data science projects with internal Global Business Organization (GBO) stakeholders to drive decisions using data analysis and modeling with both descriptive and predictive analytics.Collaborate with customers to resolve their problems and identify the best statistical techniques that can solve the problem, own the development of modeling framework.Lead gathering, extraction and compilation of data across sources via relevant tools (e.g., SQL, R, Python). Lead formatting, re-structuring, and validation of data to ensure quality and utility.Develop understanding of Google data structures, and metrics, advocating for product/Engineering changes where needed.